broom tidies 100+ models from popular modelling packages and almost all of the model objects in the stats package that comes with base R. vignette("available-methods") lists method availabilty.

If you aren’t familiar with tidy data structures and want to know how they can make your life easier, we highly recommend reading Hadley Wickham’s Tidy Data.

Installation

# we recommend installing the entire tidyverse modeling set, which includes broom:install.packages("tidymodels")
# alternatively, to install just broom:install.packages("broom")
# to get the development version from GitHub:install.packages("devtools")
devtools::install_github("tidymodels/broom")

If you find a bug, please file a minimal reproducible example in the issues.

Usage

tidy() produces a tibble() where each row contains information about an important component of the model. For regression models, this often corresponds to regression coefficients. This is can be useful if you want to inspect a model or create custom visualizations.

augment adds columns to a dataset, containing information such as fitted values, residuals or cluster assignments. All columns added to a dataset have . prefix to prevent existing columns from being overwritten.

Contributing

We welcome contributions of all types!

If you have never made a pull request to an R package before, broom is an excellent place to start. Find an issue with the Beginner Friendly tag and comment that you’d like to take it on and we’ll help you get started.

We encourage typo corrections, bug reports, bug fixes and feature requests. Feedback on the clarity of the documentation is especially valuable.